Automatic boundary extraction and rectification of bony tissue in CT images using artificial intelligence techniques

Matthew F.Y. Kwan; K. C. Cheung; Ian Gibson

doi:10.1117/12.387755

Automatic boundary extraction and rectification of bony tissue in CT images using artificial intelligence techniques

Matthew F.Y. Kwan^*, K. C. Cheung, Ian Gibson

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › Academic › peer-review

2 Citations (Scopus)

34 Downloads (Pure)

Abstract

A novel approach is presented for fully automated boundary extraction and rectification of bony tissue from planar CT data. The approach extracts and rectifies feature boundary in a hierarchical fashion. It consists of a fuzzy multilevel thresholding operation, followed by a small void cleanup procedure. Then a binary morphological boundary detector is applied to extract the boundary. However, defective boundaries and undesirable artifacts may still be present. Thus two innovative anatomical knowledge based algorithms are used to remove the undesired structures and refine the erroneous boundary. Results of applying the approach on lumbar CT images are presented, with a discussion of the potential for clinical application of the approach.

Original language	English
Pages (from-to)	I/-
Journal	Proceedings of SPIE - the international society for optical engineering
Volume	3979
DOIs	https://doi.org/10.1117/12.387755
Publication status	Published - 2000
Externally published	Yes
Event	Medical Imaging 2000: Image Processing - San Diego, United States Duration: 14 Feb 2000 → 17 Feb 2000

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title = "Automatic boundary extraction and rectification of bony tissue in CT images using artificial intelligence techniques",

abstract = "A novel approach is presented for fully automated boundary extraction and rectification of bony tissue from planar CT data. The approach extracts and rectifies feature boundary in a hierarchical fashion. It consists of a fuzzy multilevel thresholding operation, followed by a small void cleanup procedure. Then a binary morphological boundary detector is applied to extract the boundary. However, defective boundaries and undesirable artifacts may still be present. Thus two innovative anatomical knowledge based algorithms are used to remove the undesired structures and refine the erroneous boundary. Results of applying the approach on lumbar CT images are presented, with a discussion of the potential for clinical application of the approach.",

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AU - Kwan, Matthew F.Y.

AU - Cheung, K. C.

AU - Gibson, Ian

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N2 - A novel approach is presented for fully automated boundary extraction and rectification of bony tissue from planar CT data. The approach extracts and rectifies feature boundary in a hierarchical fashion. It consists of a fuzzy multilevel thresholding operation, followed by a small void cleanup procedure. Then a binary morphological boundary detector is applied to extract the boundary. However, defective boundaries and undesirable artifacts may still be present. Thus two innovative anatomical knowledge based algorithms are used to remove the undesired structures and refine the erroneous boundary. Results of applying the approach on lumbar CT images are presented, with a discussion of the potential for clinical application of the approach.

AB - A novel approach is presented for fully automated boundary extraction and rectification of bony tissue from planar CT data. The approach extracts and rectifies feature boundary in a hierarchical fashion. It consists of a fuzzy multilevel thresholding operation, followed by a small void cleanup procedure. Then a binary morphological boundary detector is applied to extract the boundary. However, defective boundaries and undesirable artifacts may still be present. Thus two innovative anatomical knowledge based algorithms are used to remove the undesired structures and refine the erroneous boundary. Results of applying the approach on lumbar CT images are presented, with a discussion of the potential for clinical application of the approach.

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U2 - 10.1117/12.387755

DO - 10.1117/12.387755

M3 - Conference article

AN - SCOPUS:0033699736

SN - 0277-786X

VL - 3979

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JO - Proceedings of SPIE - the international society for optical engineering

JF - Proceedings of SPIE - the international society for optical engineering

T2 - Medical Imaging 2000: Image Processing

Y2 - 14 February 2000 through 17 February 2000

ER -

Automatic boundary extraction and rectification of bony tissue in CT images using artificial intelligence techniques

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